Counting tokens is dumb. So we built a free metric for AI proficiency.
A new metric called AIQ Rank has been developed to measure proficiency in AI coding tools like Claude Code and Codex. Unlike traditional token usage metrics, which can be misleading, AIQ Rank evaluates user activity based on various dimensions of tool customization and efficiency. This free tool aims to provide a more accurate assessment of an individual's skill in utilizing AI effectively.
- ▪AIQ Rank scores users on an observable scale from 0-1000 based on their session activity with AI coding tools.
- ▪The metric focuses on dimensions such as customization, multitasking, and planning rather than just token usage.
- ▪The tool runs locally and does not share transcripts, ensuring user privacy.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/charlie_graham_12a6bd8586/counting-tokens-is-dumb-so-we-built-a-free-metric-for-ai-proficiency-5a88 |
| Publication time | Wed, 20 May 2026 21:59:12 +0000 |
| Retrieval time | 2026-05-20T22:05:03.081Z |
| Last seen | 2026-05-20T22:05:03.081Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 3fYG7qS2MP3c |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3401276) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Charlie Graham Posted on May 20 Counting tokens is dumb. So we built a free metric for AI proficiency. #ai #programming #claude #openai We’ve been trying to figure out a real answer to a question that keeps coming up: how do you measure whether someone is actually good at Claude Code, Codex, and the other AI coding tools? Not "do they use them," but how good are they at using AI. The first metric we looked at, like everyone else, was token usage.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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